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The evolution of human cognition and its implications for instruction

John Sweller presentation at Learning through inquiry working

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Gráinne Conole
10 December 2008

John Sweller talking about the evolution of human cognition and its implication for instruction.

A lot of what is known in human cognition architecture (HCA) domain is not getting picked up in the instructional design field.

Categories of knowledge – D. Geary (2007) Educating the evolved mind – conceptual foundations for an evolutionary educational psychology in J.S, Carlson and J.R. Levin Eds) psychological perspectives on contemporary educational issues, Greenwich, CT: Information Age Publishing.


Two types of knowledge

  • Biologically primary knowledge (BPK) – evolved to acquire over a long time, we can do it easily, rapidly – such as learning a first language, same is true of learning to listen, recognising faces, general problem solving analysis. We evolve to acquire these sort of skills
  • Biologically secondary knowledge (BSK)– knowledge that has become culturally important in last 5,000 years or so, we acquire it differently, not easily or automatically or unconsciously, has different characteristics. Educational institutions were invented because of BSK. Reading and writing are obvious example of this. Knowledge needs to be taught explicitly, directly and takes an effort to acquire this form of knowledge.

What aspects of HCA apply to BSK?

Sweller, J. and Sweller, S. (2006) Natural information processing systems, Evolutionary Psychology 4, 434-458

Biological evolution is an information processes system – creates information, transmits it across time and remembers it. The processes we use can be mapped to surprising accuracy to the processes used by Darwinian evolution.


Five principles

  1. Information store principle: In evolutionary terms, DNA sequences hold masses of information and are central in terms of evolution, the equivalent in HCA is long term memory (LTM)– massive amount of information is stored in LTM, everything we do depends on that huge amount of information held. Chess player master can recognise huge chess moves and configurations. We are our LTM, cognitively at least. If nothing changes in LTM nothing has been learned.
  2. Borrowing and reorganising principle. Asexual reproduction produces an exact copy, sexual reproduction is the opposite. Cognitive equivalent? Imitating what others do, listening to others, we borrow information from other peoples’ long term stores. Writing can transmit information over a long period of time. Information is reorganised when we take it in. Not an exact copying process. We obtain most of our information from other people. But that information has to be created in the first place. How is it created?
  3. Randomness as genesis principle. In biological systems – the ultimate base for all biological variation is random mutation. What is the equivalent? How can random generation test give sophisticated complex structures. Firstly its not totally random, we use knowledge to reduce the number of options. Use knowledge as much as possible but at some point if it’s a real problem you cant go any further? The only possibility is to randomly generate a move and test it for effectiveness. If it doesn’t work, try an alternative. We have no choice but to engage in random generation. This has instructional implications.
  4. Narrow limits of change principle. If we are randomly generate moves, need some mechanism to stop computational explosion. Working memory is extremely limiting in terms of capacity, limited in terms of time span. This only applies to novel information – this also has implications for instructional design. Cognitive load theory – limitations of working memory are central to this theory. Need to take account of this in the design process. Often too much instruction design proceeds as if we don’t have working memory.
  5. Environmental organising and linking principle. The whole purpose of the system comes down to this. If working memory is dealing with familiar info from long term memory the limitations disappear, its only limited in terms of novel information. Which comes back to information story principle 1, aim is to get information into LTM, that leads to change, to learning. The purpose of instruction is to get material via working memory (which is limited when dealing with novel info) and then get into LTM and then we can do things we couldn’t do before. Changes us, who we are and what we can do. How should information be presented in spoken form, written, diagrams, etc.



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